多元正向参数覆盖面积评价模型的建立及其在油气藏流体相识别中的应用  

Establishment of a multivariate forward parameters coverage area evaluation model and its application in fluid phase identification of hydrocarbon reservoirs

作　　者：景社 王雷 于冬冬 袁胜斌 韩学彪 曹英权 JING She;WANG Lei;YU Dongdong;YUAN Shengbin;HAN Xuebiao;CAO Yingquan(China French Bohai Geoservices Co.,Ltd.,Tianjin 300457,China;Shanghai Branch of CNOOC(China)Co.,Ltd.,Shanghai 200335,China)

机构地区：[1]中法渤海地质服务有限公司 [2]中海石油(中国)有限公司上海分公司

出　　处：《录井工程》2024年第2期57-64,共8页Mud Logging Engineering

基　　金：中国海洋石油有限公司“十四五”重大科技项目“海上深层/超深层油气勘探地质作业关键技术研究”(编号:KJGG2022-0405)。

摘　　要：西湖凹陷平湖斜坡带油气藏流体类型比较复杂,结合PVT相态分析结果,储层流体以凝析气、挥发性油为主,在录测井资料响应特征上无明显差异,为井场随钻快速识别油气藏流体相带来困难。而油气藏流体相是产能评价、储量规模落实及开发方案制定的关键物性参数,传统的流体相识别方法主要是通过井下PVT取样分析获得,成本较高且存在作业风险。通过调研前人研究成果,将平湖斜坡带积累的4口井18层的PVT分析数据和算法相结合,首先利用皮尔逊积矩相关系数(PPMCC)对9种正向参数进行线性相关性分析,优选5种强相关性参数作为雷达图射线参数,建立了平湖斜坡带雷达图流体相图板,然后以油气藏流体气油比、密度为因变量,以雷达图5项正向参数覆盖面积为自变量,运用多元线性回归建立多参数气油比、密度预测模型,明确雷达图正向参数覆盖面积与油气藏气油比、密度之间的定量关系。基于PPMCC数据分析,优选C_(2)/C_(3)、(C_(1)+C_(2))/(C_(3)+C_(4)+C_(5))、C_(2)/(C_(3)+C_(4))、C_(1)/C_(3)、(C_(1)+C_(2)+C_(3))/(C_(4)+C_(5))共5项参数构成雷达图,从几何模型出发建立多参数气油比、密度预测模型。通过在5口井14层的验证应用,气油比的平均预测误差为11.55%,密度的平均预测误差为4.71%,表明所建立的模型可实现对油气藏类型快速、精确划分,应用效果明显。The fluid types of hydrocarbon reservoirs in Pinghu slope belt of Xihu sag are complicated.According to the PVT phase behavior analysis results,the reservoir fluids are mainly condensate gas and volatile oil.There is no obvious difference in the response characteristics of mud logging and well logging data,which makes it difficult to quickly identify the fluid phases of hydrocarbon reservoirs while drilling at the well site.The fluid phases of hydrocarbon reservoirs are the key physical property parameters for productivity evaluation,reserve scale implementation and development plan formulation.The traditional fluid phase identification method is mainly obtained through downhole PVT sampling analysis,with high cost and operating risk.By investigating the previous research results,the PVT analysis data from 18 layers of 4 wells accumulated in Pinghu slope belt were combined with the algorithm.First,the Pearson product⁃moment correlation coefficient(PPMCC)was used to conduct linear correlation analysis on 9 forward parameters,and 5 highly correlated parameters were optimized as radar chart ray parameters.A radar chart for fluid phases of the Pinghu slope belt was established.Then,with the gas⁃oil ratio and density of the hydrocarbon reservoir fluid as the dependent variables,and the coverage area of the five forward parameters in the radar chart as the independent variables,the multiparameter gas⁃oil ratio and density prediction models are established by using multiple linear regression to clarify the quantitative relationship between the coverage area of the forward parameters in the radar chart and the gas⁃oil ratio and density of the hydrocarbon reservoirs.Based on PPMCC data analysis,C_(2)/C_(3)、(C_(1)+C_(2))/(C_(3)+C_(4)+C_(5))、C_(2)/(C_(3)+C_(4))、C_(1)/C_(3)、(C_(1)+C_(2)+C_(3))/(C_(4)+C_(5)),a total of 5 parameters are optimized to form a radar chart.The multiparameter gas⁃oil ratio and density prediction models established from the geometric model have been verified and applied in 14 layers

关 键 词：正向参数覆盖面积法 皮尔逊积矩相关系数 雷达图 油气藏流体相 气油比 密度 西湖凹陷 

分 类 号：TE132.1[石油与天然气工程—油气勘探]